Qiyong Fan

Emission guided radiation therapy for lung and prostate cancers: a feasibility study on a digital patient.

PURPOSE Accurate tumor tracking remains a challenge in current radiation therapy. Many strategies including image guided radiation therapy alleviate the problem to certain extents. The authors propose a new modality called emission guided radiation therapy (EGRT) to accurately and directly track the tumor based on its biological signature. This work is to demonstrate the feasibility of EGRT under two clinical scenarios using a 4D digital patient model. METHODS EGRT uses lines of response (LORs) from positron emission events to direct beamlets of therapeutic radiation through the emission sites inside a tumor. This is accomplished by a radiation delivery system consisting of a Linac and positron emission tomography (PET) detectors on a fast rotating closed-ring gantry. During the treatment of radiotracer-administrated cancer patients, PET detectors collect LORs from tumor uptake sites and the Linac responds in nearly real-time with beamlets of radiation along the same LOR paths. Moving tumors are therefore treated with a high targeting accuracy. Based on the EGRT concept, the authors design a treatment method with additional modulation algorithms including attenuation correction and an integrated boost scheme. Performance is evaluated using simulations of a lung tumor case with 3D motion and a prostate tumor case with setup errors. The emission process is simulated by Geant4 Application for Tomographic Emission package (GATE) and Linac dose delivery is simulated using a voxel-based Monte Carlo algorithm (VMC++). RESULTS In the lung case with attenuation correction, compared to a conventional helical treatment, EGRT achieves a 41% relative increase in dose to 95% of the gross tumor volume (GTV) and a 55% increase to 50% of the GTV. All dose distributions are normalized for the same dose to the lung. In the prostate case with the integrated boost and no setup error, EGRT yields a 19% and 55% relative dose increase to 95% and 50% of the GTV, respectively, when all methods are normalized for the same dose to the rectum. In the prostate case with integrated boost where setup error is present, EGRT contributes a 21% and 52% relative dose increase to 95% and 50% of the GTV, respectively. CONCLUSIONS As a new radiation therapy modality with inherent tumor tracking, EGRT has the potential to substantially improve targeting in radiation therapy in the presence of intrafractional and interfractional motion.

Image-domain shading correction for cone-beam CT without prior patient information

In the era of high‐precision radiotherapy, cone‐beam CT (CBCT) is frequently utilized for on‐board treatment guidance. However, CBCT images usually contain severe shading artifacts due to strong photon scatter from illumination of a large volume and non‐optimized patient‐specific data measurements, limiting the full clinical applications of CBCT. Many algorithms have been proposed to alleviate this problem by data correction on projections. Sophisticated methods have also been designed when prior patient information is available. Nevertheless, a standard, efficient, and effective approach with large applicability remains elusive for current clinical practice. In this work, we develop a novel algorithm for shading correction directly on CBCT images. Distinct from other image‐domain correction methods, our approach does not rely on prior patient information or prior assumption of patient data. In CBCT, projection errors (mostly from scatter and non‐ideal usage of bowtie filter) result in dominant low‐frequency shading artifacts in image domain. In circular scan geometry, these artifacts often show global or local radial patterns. Hence, the raw CBCT images are first preprocessed into the polar coordinate system. Median filtering and polynomial fitting are applied on the transformed image to estimate the low‐frequency shading artifacts (referred to as the bias field) angle‐by‐angle and slice‐by‐slice. The low‐pass filtering process is done firstly along the angular direction and then the radial direction to preserve image contrast. The estimated bias field is then converted back to the Cartesian coordinate system, followed by 3D low‐pass filtering to eliminate possible high‐frequency components. The shading‐corrected image is finally obtained as the uncorrected volume divided by the bias field. The proposed algorithm was evaluated on CBCT images of a pelvis patient and a head patient. Mean CT number values and spatial non‐uniformity on the reconstructed images were used as image quality metrics. Within selected regions of interest, the average CT number error was reduced from around 300 HU to 42 and 38 HU, and the spatial nonuniformity error was reduced from above 17.5% to 2.1% and 1.7% for the pelvis and the head patients, respectively. As our method suppresses only low‐frequency shading artifacts, patient anatomy and contrast were retained in the corrected images for both cases. Our shading correction algorithm on CBCT images offers several advantages. It has a high efficiency, since it is deterministic and directly operates on the reconstructed images. It requires no prior information or assumptions, which not only achieves the merits of CBCT‐based treatment monitoring by retaining the patient anatomy, but also facilitates its clinical use as an efficient image‐correction solution. PACS number(s): 87.57.C‐, 87.57.cp, 87.57.Q‐In the era of high-precision radiotherapy, cone-beam CT (CBCT) is frequently utilized for on-board treatment guidance. However, CBCT images usually contain severe shading artifacts due to strong photon scatter from illumination of a large volume and non-optimized patient-specific data measurements, limiting the full clinical applications of CBCT. Many algorithms have been proposed to alleviate this problem by data correction on projections. Sophisticated methods have also been designed when prior patient information is available. Nevertheless, a standard, efficient, and effective approach with large applicability remains elusive for current clinical practice. In this work, we develop a novel algorithm for shading correction directly on CBCT images. Distinct from other image-domain correction methods, our approach does not rely on prior patient information or prior assumption of patient data. In CBCT, projection errors (mostly from scatter and non-ideal usage of bowtie filter) result in dominant low-frequency shading artifacts in image domain. In circular scan geometry, these artifacts often show global or local radial patterns. Hence, the raw CBCT images are first preprocessed into the polar coordinate system. Median filtering and polynomial fitting are applied on the transformed image to estimate the low-frequency shading artifacts (referred to as the bias field) angle-by-angle and slice-by-slice. The low-pass filtering process is done firstly along the angular direction and then the radial direction to preserve image contrast. The estimated bias field is then converted back to the Cartesian coordinate system, followed by 3D low-pass filtering to eliminate possible high-frequency components. The shading-corrected image is finally obtained as the uncorrected volume divided by the bias field. The proposed algorithm was evaluated on CBCT images of a pelvis patient and a head patient. Mean CT number values and spatial non-uniformity on the reconstructed images were used as image quality metrics. Within selected regions of interest, the average CT number error was reduced from around 300 HU to 42 and 38 HU, and the spatial nonuniformity error was reduced from above 17.5% to 2.1% and 1.7% for the pelvis and the head patients, respectively. As our method suppresses only low-frequency shading artifacts, patient anatomy and contrast were retained in the corrected images for both cases. Our shading correction algorithm on CBCT images offers several advantages. It has a high efficiency, since it is deterministic and directly operates on the reconstructed images. It requires no prior information or assumptions, which not only achieves the merits of CBCT-based treatment monitoring by retaining the patient anatomy, but also facilitates its clinical use as an efficient image-correction solution. PACS number(s): 87.57.C-, 87.57.cp, 87.57.Q.

A novel convolution-based approach to address ionization chamber volume averaging effect in model-based treatment planning systems.

The ionization chamber volume averaging effect is a well-known issue without an elegant solution. The purpose of this study is to propose a novel convolution-based approach to address the volume averaging effect in model-based treatment planning systems (TPSs). Ionization chamber-measured beam profiles can be regarded as the convolution between the detector response function and the implicit real profiles. Existing approaches address the issue by trying to remove the volume averaging effect from the measurement. In contrast, our proposed method imports the measured profiles directly into the TPS and addresses the problem by reoptimizing pertinent parameters of the TPS beam model. In the iterative beam modeling process, the TPS-calculated beam profiles are convolved with the same detector response function. Beam model parameters responsible for the penumbra are optimized to drive the convolved profiles to match the measured profiles. Since the convolved and the measured profiles are subject to identical volume averaging effect, the calculated profiles match the real profiles when the optimization converges. The method was applied to reoptimize a CC13 beam model commissioned with profiles measured with a standard ionization chamber (Scanditronix Wellhofer, Bartlett, TN). The reoptimized beam model was validated by comparing the TPS-calculated profiles with diode-measured profiles. Its performance in intensity-modulated radiation therapy (IMRT) quality assurance (QA) for ten head-and-neck patients was compared with the CC13 beam model and a clinical beam model (manually optimized, clinically proven) using standard Gamma comparisons. The beam profiles calculated with the reoptimized beam model showed excellent agreement with diode measurement at all measured geometries. Performance of the reoptimized beam model was comparable with that of the clinical beam model in IMRT QA. The average passing rates using the reoptimized beam model increased substantially from 92.1% to 99.3% with 3%/3 mm and from 79.2% to 95.2% with 2%/2 mm when compared with the CC13 beam model. These results show the effectiveness of the proposed method. Less inter-user variability can be expected of the final beam model. It is also found that the method can be easily integrated into model-based TPS.

Toward a planning scheme for emission guided radiation therapy (EGRT): FDG based tumor tracking in a metastatic breast cancer patient.

PURPOSE Emission guided radiation therapy (EGRT) is a new modality that uses PET emissions in real-time for direct tumor tracking during radiation delivery. Radiation beamlets are delivered along positron emission tomography (PET) lines of response (LORs) by a fast rotating ring therapy unit consisting of a linear accelerator (Linac) and PET detectors. The feasibility of tumor tracking and a primitive modulation method to compensate for attenuation have been demonstrated using a 4D digital phantom in our prior work. However, the essential capability of achieving dose modulation as in conventional intensity modulated radiation therapy (IMRT) treatments remains absent. In this work, the authors develop a planning scheme for EGRT to accomplish sophisticated intensity modulation based on an IMRT plan while preserving tumor tracking. METHODS The planning scheme utilizes a precomputed LOR response probability distribution to achieve desired IMRT planning modulation with effects of inhomogeneous attenuation and nonuniform background activity distribution accounted for. Evaluation studies are performed on a 4D digital patient with a simulated lung tumor and a clinical patient who has a moving breast cancer metastasis in the lung. The Linac dose delivery is simulated using a voxel-based Monte Carlo algorithm. The IMRT plan is optimized for a planning target volume (PTV) that encompasses the tumor motion using the MOSEK package and a Pinnacle3™ workstation (Philips Healthcare, Fitchburg, WI) for digital and clinical patients, respectively. To obtain the emission data for both patients, the Geant4 application for tomographic emission (GATE) package and a commercial PET scanner are used. As a comparison, 3D and helical IMRT treatments covering the same PTV based on the same IMRT plan are simulated. RESULTS 3D and helical IMRT treatments show similar dose distribution. In the digital patient case, compared with the 3D IMRT treatment, EGRT achieves a 15.1% relative increase in dose to 95% of the gross tumor volume (GTV) and a 31.8% increase to 50% of the GTV. In the patient case, EGRT yields a 15.2% relative increase in dose to 95% of the GTV and a 20.7% increase to 50% of the GTV. The organs at risk (OARs) doses are kept similar or lower for EGRT in both cases. Tumor tracking is observed in the presence of planning modulation in all EGRT treatments. CONCLUSIONS As compared to conventional IMRT treatments, the proposed EGRT planning scheme allows an escalated target dose while keeping dose to the OARs within the same planning limits. With the capabilities of incorporating planning modulation and accurate tumor tracking, EGRT has the potential to greatly improve targeting in radiation therapy and enable a practical and effective implementation of 4D radiation therapy for planning and delivery.

SU‐HH‐BRB‐06: Emission Guided Radiation Therapy: A Simulation Study of Treatment without Margin

Purpose: Accurate tumor tracking remains as a major challenge in radiation therapy. Margins are added to the clinical target volume (CTV) to ensure the treatment of tumor in the presence of patient setup uncertainty. Fiducial seeds and calypso markers are commonly implanted into the disease sites to further reduce the dosedelivery error due to tumor motion. For more accurate dosedelivery and improved patient comfort, the use of radioactive tracers in positron emission tomography(PET) as non‐invasive tumor markers has been proposed ‐ a concept called emission‐guided radiation therapy (EGRT). Method and Materials: Instead of using images obtained from a stand‐alone PET scanner for treatment guidance, we mount a positronimaging system on a radiation therapy machine. Such an EGRT system is able to track the tumor in real time based on the lines of response (LOR) of the tumorpositron events, and perform radiation therapy simultaneously. One main algorithmic difficulty of EGRT implementation is how to deliver the dose based on an existing treatment plan and the acquired real‐time tumor location information. In this work, we illustrate the EGRT concept using computer simulations and propose an adaptive algorithm for dosedelivery.Results: EGRTs advantage on increased dosedelivery accuracy is demonstrated using a prostate treatment case without the setup margin. The emission process is simulated by Geant4 Application for Tomographic Emission package and Linac dosedelivery is simulated using a voxel‐based Monte Carlo algorithm. A treatment setup error of 1cm is simulated on the prostate. The dose distributions show that the proposed EGRT can accurately deliver the prescribed dose to the CTV without using margins to compensate for the setup error. Conclusion: Although still in a preliminary research stage, EGRT has the potential to substantially reduce tumor location uncertainties and to greatly increase the performance of current radiation therapy.

TU‐G‐BRA‐04: Emission Guided Radiation Therapy: A Simulation Study of Lung Cancer Treatment with Automatic Tumor Tracking Using a 4D Digital Patient Model

Purpose: Accurate tumor tracking, especially for lungcancer, remains a challenge ineffectively addressed. Many strategies including respiratory gating and fiducial implanting alleviate the problem to different extents however they are sub‐optimal due to indirect tracking. To track the tumor itself, the concept of Emission Guided Radiation therapy(EGRT) was recently proposed. This work serves to demonstrate the feasibility of the EGRT concept within the context of lungcancertreatment.Methods: EGRT is based on the physics principle that lines of response(LORs) from positron emission events can define the lines of radiation projection passing through the emission sites. It enlightens the design of a radiation delivery system consisting of a linac and PETdetectors on a fast rotating closed‐ring gantry. When treating radiotracer administrated patients, PETdetectors collect LORs from tumor uptake sites and the linac responds simultaneously with beamlets of radiation along the same LOR paths. Accurate direct tumor tracking can automatically be achieved with real‐time responses. To validate the EGRT concept, a treatment scheme is designed and implemented for the 4D XCAT phantom with a lungtumor. A conventional treatment is modeled for comparison. Attenuation correction is also implemented in EGRT. The emission process is simulated by Geant4 Application for Tomographic Emission package(GATE) and linacdose delivery is simulated using a voxel‐based Monte Carlo algorithm(VMC++). Results: EGRT, with or without attenuation correction, achieves over 25% and 40% relative dose increase to 100% and 50% of the tumor volume respectively compared to the conventional treatment with all cases normalized to have the same integral dose to lung. Attenuation correction helps achieve a better dose performance. Dose‐peaking in the tumor volume is observed in EGRT, demonstrating automatic tumor tracking. Conclusions: As a new radiation therapy modality with inherent tumor tracking, EGRT has the potential to substantially improve radiation therapy for lungcancer. This study was funded by RefleXion Medical, a company commercializing PET‐guided radiotherapy. SRM, ASN and LZ have financial interest in RefleXion.

Priori mask guided image reconstruction (p-MGIR) for ultra-low dose cone-beam computed tomography

Recently, the compressed sensing (CS) based iterative reconstruction method has received attention because of its ability to reconstruct cone beam computed tomography (CBCT) images with good quality using sparsely sampled or noisy projections, thus enabling dose reduction. However, some challenges remain. In particular, there is always a tradeoff between image resolution and noise/streak artifact reduction based on the amount of regularization weighting that is applied uniformly across the CBCT volume. The purpose of this study is to develop a novel low-dose CBCT reconstruction algorithm framework called priori mask guided image reconstruction (p-MGIR) that allows reconstruction of high-quality low-dose CBCT images while preserving the image resolution. In p-MGIR, the unknown CBCT volume was mathematically modeled as a combination of two regions: (1) where anatomical structures are complex, and (2) where intensities are relatively uniform. The priori mask, which is the key concept of the p-MGIR algorithm, was defined as the matrix that distinguishes between the two separate CBCT regions where the resolution needs to be preserved and where streak or noise needs to be suppressed. We then alternately updated each part of image by solving two sub-minimization problems iteratively, where one minimization was focused on preserving the edge information of the first part while the other concentrated on the removal of noise/artifacts from the latter part. To evaluate the performance of the p-MGIR algorithm, a numerical head-and-neck phantom, a Catphan 600 physical phantom, and a clinical head-and-neck cancer case were used for analysis. The results were compared with the standard Feldkamp-Davis-Kress as well as conventional CS-based algorithms. Examination of the p-MGIR algorithm showed that high-quality low-dose CBCT images can be reconstructed without compromising the image resolution. For both phantom and the patient cases, the p-MGIR is able to achieve a clinically-reasonable image with 60 projections. Therefore, a clinically-viable, high-resolution head-and-neck CBCT image can be obtained while cutting the dose by 83%. Moreover, the image quality obtained using p-MGIR is better than the quality obtained using other algorithms. In this work, we propose a novel low-dose CBCT reconstruction algorithm called p-MGIR. It can be potentially used as a CBCT reconstruction algorithm with low dose scan requests.

SU‐E‐T‐584: Optical Tracking Guided Patient‐Specific VMAT QA with ArcCHECK

Purpose: To investigate the novel use of an in-house optical tracking system (OTS) to improve the efficacy of VMAT QA with a cylindrical dosimeter (ArcCHECK™). Methods: The translational and rotational setup errors of ArcCHECK are convoluted which makes it challenging to position the device efficiently and accurately. We first aligned the ArcCHECK to the machine cross-hair at three cardinal angles (0°, 90°, and 270°) to establish a reference position. Four infrared reflective markers were attached to the back of the device. An OTS with 0.2mm/0.2° accuracy was used to control its setup uncertainty. Translational uncertainties of 1 mm and 2 mm in three directions (in, right, and up) were applied on the device. Four open beams of various field sizes and six clinical VMAT arcs were delivered and measured for all simulated setup errors. The measurements were compared with Pinnacle™ calculations using Gamma analysis to evaluate the impact of setup uncertainty. This study also evaluated the improvement in setup reproducibility and efficiency with the aid of the OTS. Results: For open beams, with 3%/3mm, the mean passing rates dropped by less than 5% for all shifts; with 2%/2mm, two significant drops(>5%) were observed: 15.38±6.75% for 2 mm lateral shift and 9.35±4.88% for 2 mm longitudinal shift. For VMAT arcs, the mean passing rates using 2%/2mm dropped by 10.47±7.46% and 22.02±11.39% for 1 and 2 mm shift, respectively. With 3%/3mm, significant drop only occurred with 2 mm longitudinal shift (13.73±8.30%). Setup time could be reduced by >15 min with the aid of the OTS. Conclusion: OTS is an effective tool for separating translational and rotational uncertainties. The current VMAT QA solution was not strongly sensitive to translation errors of 2mm with widely accepted criterion (3%/3mm). This finding raises concerns regarding the efficacy of such QA system in detecting errors in the dynamic VMAT delivery.

Application of statistical and computational methodology to predict brainstem dosimetry for trigeminal neuralgia stereotactic radiosurgery

OBJECTIVES To apply advanced statistical and computational methodology in evaluating the impact of anatomical and technical variables on normal tissue dosimetry of trigeminal neuralgia (TN) stereotactic radiosurgery (SRS). METHODS Forty patients treated with LINAC-based TN SRS with 90 Gy maximum dose were randomly selected for the study. Parameters extracted from the treatment plans for the study included three dosimetric output variables: the maximum dose to the brainstem (BSmax), the volume of brainstem that received at least 10 Gy (V10BS), and the volume of normal brain that received at least 12 Gy (V12). We analyzed five anatomical variables: the incidence angle of the nerve with the brainstem surface (A), the nerve length (L), the nerve width as measured both axially (WA) and sagittally (WS), the distance measured along the nerve between the isocenter and the brainstem surface (D), and one technical variable: the utilized cone size (CS). Univariate correlation was calculated for each pair among all parameters. Multivariate regression models were fitted for the output parameters using the optimal input parameters selected by the Gaussian graphic model LASSO. Repeated twofold cross-validations were used to evaluate the models. RESULTS Median BSmax, V10BS, and V12 for the 40 patients were 35.7 Gy, 0.14 cc, and 1.28 cc, respectively. Median A, L, WA, WS, D, and CS were 43.7°, 8.8 mm, 2.8 mm, 2.7 mm, 4.8 mm, and 6 mm, respectively. Of the three output variables, BSmax most strongly correlated with the input variables. Specifically, it had strong, negative correlations with the input anatomical variables and a positive correlation with CS. The correlation between D and BSmax at -0.51 was the strongest correlation between single input and output parameters, followed by that between CS and V10BS at 0.45, and that between A and BSmax at -0.44. V12 was most correlated with cone size alone, rather than anatomy. LASSO identified an optimal 3-feature combination of A, D, and CS for BSmax and V10BS prediction. Using cross-validation, the multivariate regression models with the three selected features yielded stronger correlations than the correlation between the BSmax and V10BS themselves. CONCLUSIONS For the first time, an advanced statistical and computational methodology was applied to study the impact of anatomical and technical variables on TN SRS. The variables were found to impact brainstem doses, and reasonably strong correlation models were established using an optimized 3-feature combination including the nerve incidence angle, cone size, and isocenter-brainstem distance.

Image-Guided High-Dose Rate Brachytherapy in Cervix Carcinoma Using Balloon Catheter and Belt Immobilization System

Purpose: The efficacy of image-guided high-dose rate brachytherapy for cervical cancer is limited by the ineffective rectal sparing devices available commercially and the potential applicator movement. We developed a novel device using a balloon catheter and a belt immobilization system, serving for rectal dose reduction and applicator immobilization purposes, respectively. Methods: The balloon catheter is constructed by gluing a short inflatable tube to a long regular open-end catheter. Contrast agent (10) cm3 is injected into the inflatable end, which is affixed to the tandem and ring applicator, to displace the posterior vaginal wall. The belt immobilization system consists of a specially designed bracket that can hold and fix itself to the applicator, a diaper-like Velcro fastener package used for connecting the patient’s pelvis to the bracket, and a buckle that holds the fasteners to stabilize the whole system. The treatment data for 21 patients with cervical cancer using both balloon catheter and belt immobilization system were retrospectively analyzed. Computed tomography and magnetic resonance images, acquired about 30 minutes apart, were registered to evaluate the effectiveness of the immobilization system. Results: In comparison with a virtual rectal blade, the balloon decreased the rectal point dose by 34% ± 4.2% (from 276 ± 57 to 182 ± 38 cGy), corresponding to an extra sparing distance of 7.9 ± 1.1 mm. The maximum sparing distance variation per patient is 1.4 ± 0.6 mm, indicating the high interfractional reproducibility for rectum sparing. With the immobilization system, the mean translational and rotational displacements of the applicator set are <3 mm and <1.5°, respectively, in all directions. Conclusions: The rectal balloon provides significant dose reduction to the rectum and it may potentially minimize patient discomfort. The immobilization system permits almost no movement of the applicator during treatment. This work has the potential to be promoted as a standardized solution for high-dose rate treatment of cervical cancer.